Abstract 5794: Gene expression analysis of appendiceal adenocarcinomas highlights tumor heterogeneity between high and low-grade
Authors: Yue Gu, Abdelrahman M. Yousef, Saikat Chowdhury, John Paul Shen
Journal: Cancer Research (2022)

Abstract Background: Current national guidelines still suggest that appendiceal cancer be treated similarly to colorectal cancer (CRC) despite clear differences between the two in terms of both clinical and molecular features. The rarity of appendiceal neoplasms has made it difficult to conduct prospective or randomized clinical trials to guide therapy for these tumors; this issue is confounded by the fact that much heterogeneity exists between multiple histopathologic subtypes. Low-grade and high-grade appendiceal tumors have marked contrast in the natural history (5-year OS 68% for low-grade vs. 7% for high-grade) and response to chemotherapy. Here we perform RNA sequencing to systematically evaluate key molecular differences between high-grade and low-grade appendiceal tumors with the goal of identifying new opportunities for therapeutic intervention in each. Methods: Whole transcriptomic RNA sequences (n = 12) of appendiceal adenocarcinomas (AA) patients’ FFPE tissues from MD Anderson Cancer Center were collected. STAR Alignment pipeline was first conducted to raw RNA-seq to generate the gene count matrix of the patients. Unsupervised clustering of the AA samples based on Euclidean-distance and Wald’s method was generated. The cohort was then divided into high-grade (n = 6) and low-grade tumor (n = 6) groups and differential gene expression analysis was performed with DESeq2 and edgeR R packages. Additionally, Gene Set Enrichment Analysis (GSEA) with hallmark and C6 gene sets was implemented to study the up/down-regulation patterns of the gene pathway in each AA cohort. Results: Unsupervised clustering of high and low-grade tumors showed clear separation by grade, with well and moderately differentiated tumors clustering separately from high-grade appendiceal adenocarcinoma. Differences in gene expression between high-grade and low-grade tumors identified that TNFa signaling via NFkB (NES = 2.23, FDR q-val &amp;lt; 0.01), MYC (NES = 1.98, FDR q-val &amp;lt; 0.01), P53 pathway (NES = 1.96, FDR q-val &amp;lt; 0.01), E2F (NES = 1.86, FDR q-val &amp;lt; 0.01) and KRAS upregulated gene set (NES = 1.38, FDR q-val = 0.068) were enriched in high-grade relative to low-grade tumors; Myogenesis (NES = -1.48, FDR q-val = 0.06) and Spermatogenesis (NES = -1.47, FDR q-val = 0.05) were depleted in high-grade relative to low-grade tumors. Conclusions: Our study demonstrates that the appendiceal tumor grades are critical to help guide towards better treatments of each subgroup. Both unsupervised clustering analysis and GSEA show different gene expression patterns between high-grade and low-grade appendiceal adenocarcinomas. Given appendiceal adenocarcinoma is a rare and heterogeneous tumor, tumor-grade-specific prognostic-predictive factors are pending investigations. Citation Format: Yue Gu, Abdelrahman M. Yousef, Saikat Chowdhury, John Paul Shen. Gene expression analysis of appendiceal adenocarcinomas highlights tumor heterogeneity between high and low-grade [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5794.